An Empirical Look at the Controversy Surrounding the Nobel Prize for Magnetic Resonance Imaging

Disputes between researchers over who deserves credit for technological breakthroughs are not unusual. Few such disputes, however, have attracted as much attention as the arguments surrounding the award of the 2003 Nobel Prize for Medicine. This prize was awarded to Paul Lauterbur and Peter Mansfield to honor “discoveries concerning the development of magnetic resonance imaging” – i.e. MRI. Soon after the award, another scientist, Raymond Damadian, took out full-page advertisements in national newspapers, decrying the award and stating that he should have been included alongside Lauterbur and Mansfield. This technical report examines Damadian’s claim from a strictly empirical perspective, by analyzing the impact of Damadian, Lauterbur, Mansfield and others on the development of MRI technology. Impact is measured via citations to their work from subsequent MRI-related patents and scientific papers. The report finds that all three scientists have had a strong impact on the development of MRI, and their early influence in this technology exceeds that of any other scientist. Damadian’s impact on MRI patents and papers was greater than that of Lauterbur and Mansfield in the initial, innovative phase of MRI technology; while Mansfield and Lauterbur (especially the former) became more influential in the growth and maturing phases. Given that the Nobel Prize can be awarded to up to three recipients, and is supposed to reward initial discoveries rather than improvements, it thus appears that, from an empirical perspective, the ‘natural’ solution would have been for all three scientists to share the award. Damadian may thus have been short-changed by the Nobel committee in its decision to omit him from the 2003 Nobel Prize for Medicine

Automatic derivation and implementation of fast convolution algorithms

This thesis surveys algorithms for computing linear and cyclic convolution. Algorithms are presented in a uniform mathematical notation that allows automatic derivation, optimization, and implementation. Using the tensor product and Chinese Remainder Theorem (CRT), a space of algorithms is defined and the task of finding the best algorithm is turned into an optimization problem over this space of algorithms. This formulation led to the discovery of new algorithms with reduced operation count. Symbolic tools are presented for deriving and implementing algorithms, and performance analyses (using both operation count and run-time as metrics) are carried out. These analyses show the existence of a window where CRT-based algorithms outperform other methods of computing convolutions. Finally a new method that combines the Fast Fourier transform with the CRT methods is derived. This latter method is shown to be faster for some very large size convolutions than either method used alone.Ph.D., Computer Science -- Drexel University, 200